import math
import os
from deployment_pima.config import config as model_config
from deployment_pima.predict import make_predictions
from deployment_pima.processing.pipeline_helper import load_data
import pandas as pd
import pytest
from api import config
_logger = config.get_logger(logger_name=__name__)
@pytest.mark.differential
def test_model_prediction_differential(
*, save_file: str = 'test_data_predictions.csv'):
"""
This test compares the prediction result similarity of
the current model with the previous model's results.
"""
# Given
# Load the saved previous model predictions
previous_model_df = pd.read_csv(
os.path.join(config.PACKAGE_ROOT, 'tests', save_file))
previous_model_predictions = previous_model_df.predictions.values
test_data = load_data(file_name=model_config.DATA_FILE)
multiple_test_input = test_data[:20]
# -*- coding: utf-8 -*-
"""
Created on Wed Aug 12 22:14:31 2020
@author: rkbra
"""
from flask import Flask
from api.config import get_logger
_logger = get_logger(logger_name=__name__)
def create_app(*, config_object) -> Flask:
"""Create a flask app instance."""
flask_app = Flask('ml_api')
flask_app.config.from_object(config_object)
# import blueprints
from api.controller import prediction_app
flask_app.register_blueprint(prediction_app)
_logger.debug('Application instance created')
return flask_app
from flask import Flask
from api.config import get_logger
_logger = get_logger(__name__)
def create_app(*,config_object) -> Flask:
flask_app = Flask('ml-api')
flask_app.config.from_object(config_object)
from api.controller import prediction_app
flask_app.register_blueprint(prediction_app)
_logger.debug('Application instance created')
return flask_app
